The first report on effect of fecal microbiota transplantation as a complementary treatment in a patient with steroid-refractory Cronkhite-Canada syndrome
Bibliographic record
Abstract
RATIONALE: Cronkhite-Canada syndrome (CCS) is a rare non-hereditary disease of unknown etiology that is characterized by the appearance of multiple polyps in the entire gastrointestinal (GI) tract, except in the esophagus, with GI and non-GI symptoms. Various factors are associated with the pathogenesis of CCS. Immune dysregulation has been discussed as one of the pathogeneses of CCS, and dysbiosis of the gut microbiota can affect the immune system. Currently, standard treatment has not been established. PATIENT CONCERNS AND DIAGNOSIS: We present the treatment with fecal microbiota transplantation (FMT) in a 67-year-old male patient with steroid-refractory CCS who could not undergo anti-tumor necrosis factor-a treatment due to suspected tuberculosis infection. INTERVENTIONS: FMT has recently attracted attention as a method of overcoming drug resistance through immunomodulatory effects through microbiome regulation. We collected the patient's stool samples before FMT and 8weeks after FMT. OUTCOMES: We analyzed the microbiome composition of patients by sequencing the V3-V4 region of the 16s rRNA gene (Miseq). After FMT, the number of episodes of diarrhea and hypoalbuminemia were also corrected. The Chao 1 index after FMT, which was significantly higher than that of donors before FMT, changed to a similar level for donors after FMT. Fusobacterium nucleatum, Pyramidobacter piscolens, and Campylobacter concisus disappeared after FMT, suggesting the presence of an association between gut microbiota and CCS. LESSONS: Furthermore, we provide the possibility that microbiome modulation by FMT could serve as a complementary treatment in patients with steroid-refractory CCS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".